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Statistical Inference for Copula-Based Regression Models

Implementing Organization

Principal Investigator
Dr. Ashok Kumar Pathak
Central University Of Punjab

Project Overview

Regression analysis is one of the widely used statistical techniques and plays a vital role in studying the dependence between response and predictor variables. Classical regression models have limited real situation applications as these models have various assumptions on the dependent variable. Copula is a powerful tool for modeling dependence among random variables. It has applications in finance, medicine, engineering, agriculture and geophysics. Copula-based regression models are more flexible and overcome several drawbacks associated with classical regression and generalized linear. The main focus of this research proposal is to develop some new, improved estimation procedures for copula-based regression models. It also aims to study the performances of proposed estimators using numerical experiments under specified and misspecified scenarios. Researchers intend to discuss various statistical properties like unbiasedness, consistency, and asymptotic properties of the estimators with real applications.

Source

Source
Science and Engineering Research Board (SERB), DST 2022-23
Funding Organization
Quick Information
Area of Research
Mathematical Sciences
Start Date
2023
End Date
2026
Status
Ongoing
Contact
ashokiitb09@gmail.com
Output
No. of Research Paper
00
Technologies (If Any)
00
No. of PhD Produced
00
Publications
00
No. of Patents
Filed : 00
Grant : 00
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